화학공학소재연구정보센터
Energy Conversion and Management, Vol.119, 422-434, 2016
Exergoeconomic analysis and multi objective optimization of performance of a Carbon dioxide power cycle driven by geothermal energy with liquefied natural gas as its heat sink
In this study a transcritical Carbon dioxide power cycle has been coupled to a liquefied natural gas to work either as the cold source and to further enhance to generate electricity. The detailed thermodynamic analysis is performed in order to investigate the effect of key parameters on the cycle performance. Also, heat exchangers are measured to find the heat transfer surface area for economic evaluation. To investigate the aforementioned cycle and for optimization purposes, an exergoeconomic analysis is done to know the important components with respect to exergoeconomic criterion. The exergoeconomic analysis reveals that Carbon dioxide turbine and condenser have the highest rate of sum cost rate associated with capital investment and the cost of exergy destruction and special attention should be paid to these components. The parametric analysis shows that there is an optimum turbine inlet pressure which brings about the highest exergy efficiency and lowest product cost rate. Moreover, the condensate pressure has the highest effect on system exergy efficiency compared to others. With the help of multi-objective optimization, the cumulative effects of these variables are investigated on the system to maximize the exergetic efficiency and to minimize the product cost rate of the system. Results show that the system is capable of producing power with exergy efficiency and product cost rate equal to 20.5% and 263592.15 $/year, respectively, according to technique for order of preference by similarity to ideal solution decision making technique. Also, the system exergy efficiency of 22.1% and 295001.26 $/year product cost rate is achieved through linear programming techniques for multidimensional analysis of preference technique and 23.97% exergy efficiency and 370378.758 $/year product cost rate is given with FUZZY decision making technique. (C) 2016 Elsevier Ltd. All rights reserved.